Issue 8, 2022

A novel electrochemical sandwich-like immunosensor based on carboxyl Ti3C2Tx MXene and rhodamine b/gold/reduced graphene oxide for Listeria monocytogenes

Abstract

Listeria monocytogenes (LM) is one of the most common food-borne pathogens and can induce a series of diseases with a high mortality rate to humans; hence, it is very necessary to develop a highly sensitive method for LM detection. Based on this need, a new sandwich-like electrochemical immunosensing platform was developed herein by preparing carboxyl Ti3C2Tx MXene (C-Ti3C2Tx MXene) as the sensing platform and rhodamine b/gold/reduced graphene oxide (RhB/Au/RGO) as the signal amplifier. The high conductivity and large surface area of C-Ti3C2Tx MXene make it a desirable nanomaterial to fix the primary antibody of LM (PAb), while the prepared Au/RGO/RhB nanohybrid is dedicated to assembling the secondary antibody (SAb) of LM, offering an amplified response signal. Through the use of RhB molecule as the signal probe, the experiments showed that the peak currents of RhB increase along with an increase in the concentration of LM from 10 to 105 CFU mL−1, and an extremely low limit of detection (2 CFU mL−1) was obtained on the basis of the proposed immunosensing platform after optimizing various conditions. Hence, it is confirmed that the developed sandwich-like immunosensor based on C-Ti3C2Tx MXene and RhB/Au/Gr has great application in the detection of LM and other analytes.

Graphical abstract: A novel electrochemical sandwich-like immunosensor based on carboxyl Ti3C2Tx MXene and rhodamine b/gold/reduced graphene oxide for Listeria monocytogenes

Article information

Article type
Paper
Submitted
30 Nov 2021
Accepted
20 Jan 2022
First published
27 Jan 2022
This article is Open Access
Creative Commons BY-NC license

Anal. Methods, 2022,14, 843-849

A novel electrochemical sandwich-like immunosensor based on carboxyl Ti3C2Tx MXene and rhodamine b/gold/reduced graphene oxide for Listeria monocytogenes

H. Niu, S. Cai, X. Liu, X. Huang, J. Chen, S. Wang and S. Zhang, Anal. Methods, 2022, 14, 843 DOI: 10.1039/D1AY02029C

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